结合主成分分析（PCA）、偏最小二乘法（PLS）回归与表面增强拉曼光谱（SERS）实现杀螟硫磷溶液浓度的定量分析。测量600~1800 cm-1杀螟硫磷溶液SERS，对特征峰附近的光谱分别进行一阶导数绝对值、多元散射校正（MSC）与标准正态变换等预处理；利用PCA与PLS回归构建浓度预测模型。通过分组交替法检验模型性能，发现MSC处理后的光谱建立模型的预测准确度最高，分析精度满足杀螟硫磷的检测要求。

Principal component analysis (PCA), partial least squares (PLS) regression and surface-enhanced Raman spectroscopy (SERS) are used in quantitative analysis of the concentration of fenitrothion solution. 600~1800 cm-1 SERS spectra of the fenitrothion solution are measured. The spectra around characteristic peaks are preprocessed by the absolute value of the first derivative, the multiplicative scatter correction (MSC) and the standard normal transformation respectively. Models are built by PCA and PLS regression. Grouping alternating method is used to validate the performance of models. It is found that the model built with the MSC preprocessed spectra performs better. The accuracy of analysis meets the detecting requirement of fenitrothion.